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AWS Textract (version v1.*.*)

analyze_document

Analyzes an input document for relationships between detected items.
The types of information returned are as follows:
Words and lines that are related to nearby lines and words. The related information is returned in two Block objects each of type KEY_VALUE_SET: a KEY Block object and a VALUE Block object. For example, Name: Ana Silva Carolina contains a key and value. Name: is the key. Ana Silva Carolina is the value.
Table and table cell data. A TABLE Block object contains information about a detected table. A CELL Block object is returned for each cell in a table.
Selectable elements such as checkboxes and radio buttons. A SELECTION_ELEMENT Block object contains information about a selectable element.
Lines and words of text. A LINE Block object contains one or more WORD Block objects.
You can choose which type of analysis to perform by specifying the FeatureTypes list.
The output is returned in a list of BLOCK objects.
AnalyzeDocument is a synchronous operation. To analyze documents asynchronously, use StartDocumentAnalysis.
For more information, see Document Text Analysis.

Parameters

$body

Type: object

{
"FeatureTypes" : [ "string. Possible values: TABLES | FORMS" ],
"Document" : {
"Bytes" : "A blob of base-64 encoded documents bytes. The maximum size of a document that's provided in a blob of bytes is 5 MB. The document bytes must be in PNG or JPG format. \nIf you are using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes passed using the Bytes field. ",
"S3Object" : {
"Bucket" : "The name of the S3 bucket.",
"Version" : "If the bucket has versioning enabled, you can specify the object version. ",
"Name" : "The file name of the input document. It must be an image file (.JPG or .PNG format). Asynchronous operations also support PDF files."
}
}
}

detect_document_text

Detects text in the input document. Amazon Textract can detect lines of text and the words that make up a line of text. The input document must be an image in JPG or PNG format. DetectDocumentText returns the detected text in an array of Block objects.
Each document page has as an associated Block of type PAGE. Each PAGE Block object is the parent of LINE Block objects that represent the lines of detected text on a page. A LINE Block object is a parent for each word that makes up the line. Words are represented by Block objects of type WORD.
DetectDocumentText is a synchronous operation. To analyze documents asynchronously, use StartDocumentTextDetection.
For more information, see Document Text Detection.

Parameters

$body

Type: object

{
"Document" : {
"Bytes" : "A blob of base-64 encoded documents bytes. The maximum size of a document that's provided in a blob of bytes is 5 MB. The document bytes must be in PNG or JPG format. \nIf you are using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes passed using the Bytes field. ",
"S3Object" : {
"Bucket" : "The name of the S3 bucket.",
"Version" : "If the bucket has versioning enabled, you can specify the object version. ",
"Name" : "The file name of the input document. It must be an image file (.JPG or .PNG format). Asynchronous operations also support PDF files."
}
}
}

get_document_analysis

Gets the results for an Amazon Textract asynchronous operation that analyzes text in a document.
You start asynchronous text analysis by calling StartDocumentAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartDocumentAnalysis. To get the results of the text-detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentAnalysis, and pass the job identifier (JobId) from the initial call to StartDocumentAnalysis.
GetDocumentAnalysis returns an array of Block objects. The following types of information are returned:
Words and lines that are related to nearby lines and words. The related information is returned in two Block objects each of type KEY_VALUE_SET: a KEY Block object and a VALUE Block object. For example, Name: Ana Silva Carolina contains a key and value. Name: is the key. Ana Silva Carolina is the value.
Table and table cell data. A TABLE Block object contains information about a detected table. A CELL Block object is returned for each cell in a table.
Selectable elements such as checkboxes and radio buttons. A SELECTION_ELEMENT Block object contains information about a selectable element.
Lines and words of text. A LINE Block object contains one or more WORD Block objects.
Use the MaxResults parameter to limit the number of blocks returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetDocumentAnalysis, and populate the NextToken request parameter with the token value that's returned from the previous call to GetDocumentAnalysis.
For more information, see Document Text Analysis.

Parameters

$body

Type: object

{
"NextToken" : "If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.",
"MaxResults" : "The maximum number of results to return per paginated call. The largest value that you can specify is 1,000. If you specify a value greater than 1,000, a maximum of 1,000 results is returned. The default value is 1,000.",
"JobId" : "A unique identifier for the text-detection job. The JobId is returned from StartDocumentAnalysis."
}

get_document_text_detection

Gets the results for an Amazon Textract asynchronous operation that detects text in a document. Amazon Textract can detect lines of text and the words that make up a line of text.
You start asynchronous text detection by calling StartDocumentTextDetection, which returns a job identifier (JobId). When the text detection operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartDocumentTextDetection. To get the results of the text-detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentTextDetection, and pass the job identifier (JobId) from the initial call to StartDocumentTextDetection.
GetDocumentTextDetection returns an array of Block objects.
Each document page has as an associated Block of type PAGE. Each PAGE Block object is the parent of LINE Block objects that represent the lines of detected text on a page. A LINE Block object is a parent for each word that makes up the line. Words are represented by Block objects of type WORD.
Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetDocumentTextDetection, and populate the NextToken request parameter with the token value that's returned from the previous call to GetDocumentTextDetection.
For more information, see Document Text Detection.

Parameters

$body

Type: object

{
"NextToken" : "If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.",
"MaxResults" : "The maximum number of results to return per paginated call. The largest value you can specify is 1,000. If you specify a value greater than 1,000, a maximum of 1,000 results is returned. The default value is 1,000.",
"JobId" : "A unique identifier for the text detection job. The JobId is returned from StartDocumentTextDetection."
}

start_document_analysis

Starts asynchronous analysis of an input document for relationships between detected items such as key and value pairs, tables, and selection elements.
StartDocumentAnalysis can analyze text in documents that are in JPG, PNG, and PDF format. The documents are stored in an Amazon S3 bucket. Use DocumentLocation to specify the bucket name and file name of the document.
StartDocumentAnalysis returns a job identifier (JobId) that you use to get the results of the operation. When text analysis is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you specify in NotificationChannel. To get the results of the text analysis operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentAnalysis, and pass the job identifier (JobId) from the initial call to StartDocumentAnalysis.
For more information, see Document Text Analysis.

Parameters

$body

Type: object

{
"NotificationChannel" : {
"SNSTopicArn" : "The Amazon SNS topic that Amazon Textract posts the completion status to.",
"RoleArn" : "The Amazon Resource Name (ARN) of an IAM role that gives Amazon Textract publishing permissions to the Amazon SNS topic. "
},
"DocumentLocation" : {
"S3Object" : {
"Bucket" : "The name of the S3 bucket.",
"Version" : "If the bucket has versioning enabled, you can specify the object version. ",
"Name" : "The file name of the input document. It must be an image file (.JPG or .PNG format). Asynchronous operations also support PDF files."
}
},
"ClientRequestToken" : "The idempotent token that you use to identify the start request. If you use the same token with multiple StartDocumentAnalysis requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. ",
"FeatureTypes" : [ "string. Possible values: TABLES | FORMS" ],
"JobTag" : "An identifier you specify that's included in the completion notification that's published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document, such as a tax form or a receipt, that the completion notification corresponds to."
}

start_document_text_detection

Starts the asynchronous detection of text in a document. Amazon Textract can detect lines of text and the words that make up a line of text.
StartDocumentTextDetection can analyze text in documents that are in JPG, PNG, and PDF format. The documents are stored in an Amazon S3 bucket. Use DocumentLocation to specify the bucket name and file name of the document.
StartTextDetection returns a job identifier (JobId) that you use to get the results of the operation. When text detection is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you specify in NotificationChannel. To get the results of the text detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentTextDetection, and pass the job identifier (JobId) from the initial call to StartDocumentTextDetection.
For more information, see Document Text Detection.

Parameters

$body

Type: object

{
"NotificationChannel" : {
"SNSTopicArn" : "The Amazon SNS topic that Amazon Textract posts the completion status to.",
"RoleArn" : "The Amazon Resource Name (ARN) of an IAM role that gives Amazon Textract publishing permissions to the Amazon SNS topic. "
},
"DocumentLocation" : {
"S3Object" : {
"Bucket" : "The name of the S3 bucket.",
"Version" : "If the bucket has versioning enabled, you can specify the object version. ",
"Name" : "The file name of the input document. It must be an image file (.JPG or .PNG format). Asynchronous operations also support PDF files."
}
},
"ClientRequestToken" : "The idempotent token that's used to identify the start request. If you use the same token with multiple StartDocumentTextDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. ",
"JobTag" : "An identifier you specify that's included in the completion notification that's published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document, such as a tax form or a receipt, that the completion notification corresponds to."
}